
The authors looked at different ways to build computational resources that would analyze shooting form for basketball players.
Read More...Levering machine learning to distinguish between optimal and suboptimal basketball shooting forms
The authors looked at different ways to build computational resources that would analyze shooting form for basketball players.
Read More...Validating DTAPs with large language models: A novel approach to drug repurposing
Here, the authors investigated the integration of large language models (LLMs) with drug target affinity predictors (DTAPs) to improve drug repurposing, demonstrating a significant increase in prediction accuracy, particularly with GPT-4, for psychotropic drugs and the sigma-1 receptor. This novel approach offers to potentially accelerate and reduce the cost of drug discovery by efficiently identifying new therapeutic uses for existing drugs.
Read More...Chemoreception in Aurelia aurita studied by AI-enhanced image analysis
The authors studied the chemoreception of moon jellyfish in response to food, and developed an AI tool to identify track and quantify the pulsation of swimming jellyfish.
Read More...Training neural networks on text data to model human emotional understanding
The authors train a neural network to detect text-based emotions including joy, sadness, anger, fear, love, and surprise.
Read More...Investigating the connection between free word association and demographics
Utilization of neural network to analyze Free Word Association to predict accurately age, gender, first language, and current country.
Read More...Assessing large language models for math tutoring effectiveness
Authors examine the effectiveness of Large Language Models (LLMs) like BERT, MathBERT, and OpenAI GPT-3.5 in assisting middle school students with math word problems, particularly following the decline in math performance post-COVID-19.
Read More...Environmentally-friendly graphene conductive ink using graphene powder, polystyrene, and waste oil
In this article, the authors propose an effective, environmentally-friendly method of producing conductive ink using expired waste oil, polystyrene, and graphene.
Read More...Lung cancer AI-based diagnosis through multi-modal integration of clinical and imaging data
Lung cancer is highly fatal, largely due to late diagnoses, but early detection can greatly improve survival. This study developed three models to enhance early diagnosis: an MLP for clinical data, a CNN for imaging data, and a hybrid model combining both.
Read More...Unveiling bias in ChatGPT-3.5: Analyzing constitutional AI principles for politically biased responses
Various methods exist to mitigate bias in AI models, including "Constitutional AI," a technique which guides the AI to behave according to a list of rules and principles. Lo, Poosarla, Singhal, Li, Fu, and Mui investigate whether constitutional AI can reduce bias in AI outputs on political topics.
Read More...Evaluating the effectiveness of machine learning models for detecting AI-generated art
The authors investigate how well AI-detection machine learning models can detect real versus AI-generated art across different art styles.
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